Representations for Image and Video-Based Modeling and<br/><br/>Rendering

Wednesday, May 16, 2001 - 2:00pm - 3:00pm
Keller 3-180
Richard Szeliski (Microsoft Research)
Obtaining photo-realistic geometric and photometric models is an important component of image-based rendering systems that use real-world imagery as their input. Applications of such systems include novel view generation and the mixing of live imagery with synthetic computer graphics. In this talk, I review a number of image-based representations (and their associated reconstruction algorithms) we have developed in the last few years. I begin by reviewing some recent approaches to the classic problem of recovering a depth map from two or more images. I then describe some of our newer representations and reconstruction algorithms, including volumetric representations, layered plane-plus-parallax representations (including the recovery of transparent and reflected layers), and multiple depth maps. Each of these techniques has its own strengths and weaknesses, which I will address. I will also present our work in video-based rendering, in which we synthesize novel video from short sample clips by discovering their (quasi-repetive) temporal structure.

About the Speaker

Richard Szeliski is a Senior Researcher in the Vision Technology Group at Microsoft Research, where he is pursuing research in 3-D computer vision, video scene analysis, and image-based rendering. His current focus is on constructing photorealistic 3D scene models from multiple images and video. He received a Ph.D. degree in Computer Science from Carnegie Mellon University, Pittsburgh, in 1988. He joined Microsoft Research in 1995. Prior to Microsoft, he worked at Bell-Northern Research, Schlumberger Palo Alto Research, the Artificial Intelligence Center of SRI International, and the Cambridge Research Lab of Digital Equipment Corporation.

Dr. Szeliski has published over 80 research papers in computer vision, computer graphics, medical imaging, and neural nets, as well as the book Bayesian Modeling of Uncertainty in Low-Level Vision. He is a Program Committee Chair for ICCV'2001, and is on the Editorial Board of the International Journal of Computer Vision. He has served as co-chair of the SPIE Conferences on Geometric Methods in Computer Vision, the 1999 Vision Algorithms Workshop, and as an Associate Editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence.